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In 1987 MCC (a team that later spun off into Cycorp) presented a futuristic concept in a private AI focus group gathering that is common practice today. Large network systems would be taught how to make sense of data through semantics taught by linguists, professors, psychologists, artists and anthropologists instead of mathematicians and programmers.

The result of this process is that you could query a system for “strong and daring person” and the system would return a picture of a man climbing a mountain cliff. It recognized the photo through tags that were cross-referenced with logical meanings through a language called CycL.

This concept is becoming more of a focus at Google. In the past two years several of the original members of this project began to work for or partner with Google.

Enter 2006, the year of Web 2.0. The technology has been implemented throughout the web and is known by the more common name “social networks”. It’s about how people socialize with each other through interactive systems that collect various forms of data. Companies such as flickr, youTube, blogger and mySpace have capitalized on the technology and understood it. Data can be networked through a series of tags, text, ratings, discussions and cross-links to determine their similarities and relationships with each other. As people are seemingly interacting with other people they are placing markers that allow for data to relate with other data.

Web 2.0 has been all about making it easier for people to locate content regardless of its form and making it easier for people to add and interact with data to various web systems. This is the entry point to the upcoming Semantic Web. Where the Web 2.0 has been focused on gathering information and building ties through a mixture of expert systems and non-expert users, the Semantic Web is focused on automating the collection of information and mashing up the data in an easy to understand humanized format, then presenting the information without being asked to do so.

Imagine a system that knows what information you’ll need for your Monday board meeting. Not because you programmed it to, but because it learned and logically deduced it.

It discovered through your outlook calendar when the meeting was and who would be attending. It matches process in your workflow and recently requested reports with the context of the meeting by a logical process involving keywords in your meeting request. It scans an attendee’s blog to find out that one of your business partners at the meeting has an affinity for blueberry bagels so it sends you an email suggesting you order some for your meeting. It also knows the recent concerns and buzzwords through IMs sent back and forth between you and your attendees and can detect whether the tone towards the topic is friendly or hostile, by which you are alerted on the presupposed tone of the meeting before it even begins. On top of all that, it prepares the charts and documents you are most likely going to want for that tone and sends it to you in a document through email.